---
title: "COVID-19"
output:
flexdashboard::flex_dashboard:
logo: rbmv_curve.png
orientation: rows
source_code: embed
theme: flatly
---
```{r setup, include=FALSE}
library(flexdashboard)
```
```{r, include=FALSE}
library(tidyverse)
library(lubridate)
library(rvest)
library(sf)
library(leaflet)
library(plotly)
library(rbmv)
`%<>%` <- magrittr::`%<>%`
dph_covid19_page <- read_html("http://www.publichealth.lacounty.gov/media/Coronavirus/locations.htm")
dph_covid19_tbls <- dph_covid19_page %>%
html_nodes("table") %>%
html_table()
dph_covid19_messy <- dph_covid19_tbls[[1]] %>%
repair_names() %>%
janitor::clean_names() %>%
rename(locations = x1, total_cases = x2) %>%
select(-x3)
dph_covid19_totals <- dph_covid19_messy %>%
slice(2:11)
dph_covid19_age_groups <- dph_covid19_messy %>%
slice(14:18) %>%
rename(age_group = locations) %>%
mutate(total_cases = parse_number(total_cases))
dph_covid19_gender <- dph_covid19_messy %>% slice(20:24) %>%
rename(gender = locations) %>%
mutate(total_cases = parse_number(total_cases))
lac_total_cases <- parse_number(dph_covid19_totals$total_cases[[1]])
lac_total_deaths <- parse_number(dph_covid19_totals$total_cases[[6]])
dph_covid19_totals %>%
mutate(locations = str_remove_all(locations, "- ")) %>%
filter(locations %in% c("Long Beach", "Pasadena")) %>%
slice(1:2) %>%
mutate(locations = str_glue("City of {locations}") %>% parse_character(),
total_cases = parse_number(total_cases)) -> lb_pass
dph_covid19 <- dph_covid19_messy %>% slice(30:365) %>%
mutate(
locations = str_remove_all(locations, regex("\\*")),
total_cases = parse_number(total_cases, na = "--"),
locations = case_when(
str_detect(locations, "San Francisquito") ~ "Unincorporated - San Francisquito Canyon/Bouquet Canyon",
TRUE ~ locations)) %>%
filter(!locations == "Los Angeles") %>%
bind_rows(., lb_pass)
captions <- dph_covid19_page %>%
html_nodes("caption") %>%
html_text()
str_remove_all(captions[1], "\\r|\\n|\\t") %>%
str_split_fixed(., "\\*", 2) -> page_updated
page_updated <- str_split_fixed(page_updated[1], " ", 4)[4]
page_updated <- str_glue("{page_updated}/20")
page_updated <- parse_date(page_updated, "%m/%d/%y")
# uncomment line below if the 'caption' html is not updated on DPH website
page_updated <- Sys.Date()
page_updated_string <- str_glue("{wday(page_updated, label = T)} {month(page_updated, label = T)} {day(page_updated)}, {year(page_updated)}")
gis <- st_read(
dsn = "data/gis/geo_export_871186bb-3266-4a1c-a0f6-8cda86b55d55.shp",
layer = "geo_export_871186bb-3266-4a1c-a0f6-8cda86b55d55",
quiet = T
)
gis %<>% st_transform(crs = 4326)
health_profile <- read_csv("data/Los_Angeles_County_City_and_Community_Health_Profiles_2018.csv")
lac_covid19 <- gis %>%
left_join(., dph_covid19, by = c("label" = "locations")) %>%
left_join(., health_profile, by = c("lcity" = "GEONAME")) %>%
mutate(total_cases = if_else(is.na(total_cases), 0, total_cases))
covid19_cases <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv")
covid19_deaths <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv")
world <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/04-18-2020.csv")
world %<>% rename(long = Long_, lat = Lat)
covid19_time_series_cases <- covid19_cases %>%
filter(Admin2 == "Los Angeles") %>%
gather("date", "cases", 12:ncol(covid19_cases)) %>%
select(Admin2, date, cases) %>%
rename(county = Admin2) %>%
mutate(date = parse_date(date, "%m/%d/%y"),
case_type = "New Confirmed Case") %>%
bind_rows(
tribble(
~county, ~date, ~cases, ~case_type,
"Los Angeles", page_updated, lac_total_cases, "New Confirmed Case")) %>%
distinct()
covid19_time_series_deaths <- covid19_deaths %>%
filter(Admin2 == "Los Angeles") %>%
gather("date", "cases", 13:ncol(covid19_deaths)) %>%
select(Admin2, date, cases) %>%
rename(county = Admin2) %>%
mutate(date = parse_date(date, "%m/%d/%y"),
case_type = "Death") %>%
bind_rows(
tribble(
~county, ~date, ~cases, ~case_type,
"Los Angeles", page_updated, lac_total_deaths, "Death")) %>%
distinct()
covid19_time_series <- bind_rows(covid19_time_series_cases, covid19_time_series_deaths)
outbreaks <- c(
"New York City, New York, US", "Nassau, New York, US", "Suffolk, New York, US",
"Westchester, New York, US", "Cook, Illinois, US", "Wayne, Michigan, US",
"Bergen, New Jersey, US", "Hudson, New Jersey, US",
"Essex, New Jersey, US")
covid19_cases_top10_us <- covid19_cases %>%
filter(Combined_Key %in% outbreaks) %>%
gather("date", "cases", 12:ncol(covid19_cases)) %>%
select(Combined_Key, date, cases) %>%
rename(location = Combined_Key) %>%
mutate(date = parse_date(date, "%m/%d/%y"),
case_type = "New Confirmed Case") %>%
distinct() %>%
arrange(date, desc(cases))
light_blue <- rbmv_pal("main", plotly = T)[1]
ruby <- rbmv_pal("main", plotly = T)[2]
pale_black <- rbmv_pal("main", plotly = T)[5]
```
LA County {data-icon="fa-map"}
=====================================
Row {data-height=505}
-------------------------------------
###
```{r}
bins <- c(0, 25, 50, 75, 100, 150, 200, 250, 300, 350, 400, Inf)
pal <- colorBin(
palette = rbmv_pal("spectrum", plotly = T),
domain = lac_covid19$total_cases,
bins = bins)
mapbox <- "https://api.mapbox.com/styles/v1/robertmitchellv/cipr7teic001aekm72dnempan/tiles/256/{z}/{x}/{y}@2x?access_token=pk.eyJ1Ijoicm9iZXJ0bWl0Y2hlbGx2IiwiYSI6ImNpcHI2cXFnbTA3MHRmbG5jNWJzMzJtaDQifQ.vtvgLokcc_EJgnWVPL4vXw"
label <- str_glue("{lac_covid19$label}
Total cases: {lac_covid19$total_cases}") %>%
lapply(htmltools::HTML)
lac_covid19 %>%
leaflet() %>%
addTiles(mapbox, attribution = paste("Data from Los Angeles County Department of Publich Health COVID-19 location table")) %>%
addPolygons(
fillColor = ~pal(total_cases),
weight = 1.5,
fillOpacity = 0.7,
smoothFactor = 0.5,
color = "white",
label = label,
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")) %>%
addLegend(
pal = pal, values = ~total_cases, opacity = 0.7,
title = NULL, position = "bottomright") %>%
setView(-118.2, 34, zoom = 9.5)
```
Row {data-height=320}
-------------------------------------
###
```{r}
source <- list(
x = 1, y = -0.24, text = "Source: 2019 Novel Coronavirus COVID-19 (2019-nCoV)\nData Repository by Johns Hopkins CSSE",
showarrow = F, xref = "paper", yref = "paper", xanchor = "right", yanchor = "auto",
xshif = 0, yshift = 0, font = list(size = 9, color = "grey")
)
covid19_cases_top10_us %>%
plot_ly(x = ~date, y = ~cases, color = ~location, line = list(color = rbmv_pal(plotly = T)[3], width = .75),
type = "scatter", mode = "lines", hoverinfo = "text",
text = ~paste(" Location: ", location,
" Case type: ", case_type,
" Cases: ", scales::comma(cases))) %>%
add_trace(x = ~date, y = ~cases, color = ~county, line = list(color = rbmv_pal(plotly = T)[2], width = 2),
data = covid19_time_series_cases, hoverinfo = "text",
text = ~paste(" Location: ", county,
" Case type: ", case_type,
" Cases: ", scales::comma(cases))) %>%
layout(title = " ",
xaxis = list(title = " "),
yaxis = list(title = "Log(Cases)\n", type = "log"),
margin = list(b = 50),
legend = list(
title = list(text = " How LA County's COVID-19 Cases Compare Across the US "),
x = 100, y = .99, font = list(size = 9)),
annotations = source) %>%
config(displayModeBar = FALSE)
```
Row {data-height=175}
-------------------------------------
###
```{r}
valueBox(page_updated_string, color = light_blue, icon = "fa-calendar", caption = "Data pulled from both LAC DPH and John Hopkins CSSE")
```
###
```{r}
total_cases <- scales::comma(last(covid19_time_series_cases$cases))
valueBox(total_cases, color = ruby, icon = "fa-ambulance", caption = "Total Lab Confirmed COVID-19 Cases in LAC")
```
###
```{r}
total_deaths <- scales::comma(last(covid19_time_series_deaths$cases))
valueBox(total_deaths, color = pale_black, icon = "fa-medkit", caption = "Total COVID-19 Related Deaths")
```
Global {data-icon="fa-globe"}
=====================================
###
```{r}
bins <- c(0, 3000, 6000, 9000, 12000, 30000, 60000, 90000, 120000, Inf)
pal <- colorBin(
palette = rbmv_pal("spectrum", plotly = T),
domain = world$Confirmed,
bins = bins)
label <- str_glue("Location: {world$Combined_Key}
Cases: {scales::comma(world$Confirmed)}
Deaths: {scales::comma(world$Deaths)}
Recovered: {scales::comma(world$Recovered)}") %>%
lapply(htmltools::HTML)
world %>%
leaflet() %>%
addTiles(mapbox, attribution = paste("Data from Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE")) %>%
addCircleMarkers(
lng = ~long, lat = ~lat,
label = ~label,
color = ~pal(Confirmed),
radius = ~ifelse(Confirmed >= 30000, 25, 15),
stroke = FALSE, fillOpacity = .7,
clusterOptions = markerClusterOptions(
showCoverageOnHover = FALSE),
labelOptions = labelOptions(
style = list("font-weight" = "normal", padding = "3px 8px"),
textsize = "15px",
direction = "auto")) %>%
addLegend(title = "COVID-19 Cases", opacity = 0.6, pal = pal, values = ~Confirmed, position = "bottomright")
```
